CS 70 at UC Berkeley

Discrete Mathematics and Probability Theory

Lecture: MTWTH 3-430pm, Zoom

Instructor Amin Ghafari

amin.ghafari (at) berkeley (dot) edu

Office Hours: MTH 10-11 pm

Instructor Khalil Sarwari

khalil.sarwari (at) berkeley (dot) edu

Office Hours: MW 5-6 pm

Instructor Yining Liu

lyining (at) berkeley (dot) edu

Office Hours: WF 9-10 am


There is no textbook for this class. Instead, there is a set of comprehensive lecture notes. Make sure you revisit the notes after every lecture, and multiple times thereafter: you should be aware that it will likely take several readings before you fully understand the material. Each note may be covered in one or more lectures. See Policies for more information.



Discussions will be held over Zoom. The discussion sections are specifically designed to consolidate the material covered in lectures and in the notes. It is highly recommended that you attend all discussions each week. You should attend the discussion that you signed up for, since attendance for that discussion will be graded. All sections are equivalent: they all cover the same material. See Policies for more information.



There will be weekly required homeworks (9 total, including a Homework 0), again designed to consolidate your understanding of the course material. It is highly recommended that you attempt all homeworks. Your lowest homework score will be dropped, but this drop should be reserved for emergencies. No additional allowances will be made for late or missed homeworks: please do not contact us about missed homeworks or late submissions. See Policies for more information.


Lecture Schedule

  • Lecture 1A (6/22): Introduction & Logic (full)
  • Lecture 1B (6/23): Proofs (full)
  • Lecture 1C (6/24): Induction (full)
  • Lecture 1D (6/25): Sets, Functions (full)
  • Lecture 2A (6/29): Cardinality, Computability (full)
  • Lecture 2B (6/30): Graphs 1 (full)
  • Lecture 2C (7/1): Graphs 2 (full)
  • Lecture 2D (7/2): Modular Arithmetic 1 (full)
  • Lecture 3A (7/6): Modular Arithmetic 2 (full)
  • Lecture 3B (7/7): RSA/Crytography (full)
  • Lecture 3C (7/8): Polynomials and Secret Sharing (full)
  • Lecture 3D (7/9): Error Correcting Codes
  • Lecture cancelled (7/13): Midterm
  • Lecture 4A (7/14): Counting 1
  • Lecture 4B (7/15): Counting 2
  • Lecture 4C (7/16): Intro to Discrete Probability
  • Lecture 5A (7/20): Conditional Probability, Bayes' Rule, Total Probability Rule
  • Lecture 5B (7/21): Independence, Combination of Events, Inclusion-Exclusion, Union Bound
  • Lecture 5C (7/22): Discrete Random Variables
  • Lecture 5D (7/23): Variance and Covariance
  • Lecture 6A (7/27): Distributions
  • Lecture 6B (7/28): Intro to Continuous Probability
  • Lecture 6C (7/29): Continuous Distributions
  • Lecture 6D (7/30): Joint Distributions
  • Lecture 7A (8/3): Concentration Inequalities
  • Lecture 7B (8/4): Concentration Inequalities 2
  • Lecture 7C (8/5): Markov Chains 1
  • Lecture 7D (8/6): Markov Chains 2
  • Lecture 8A (8/10): Extra
  • Lecture 8B (8/11): Extra
  • Lecture 8C (8/12): Extra
  • Lecture 8D (8/13): Final